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import gradio as gr |
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from transformers import pipeline |
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from PIL import Image |
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import torch |
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from torchvision import transforms |
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from torchvision.models import resnet50 |
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import torch.nn.functional as F |
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text_emotion_pipeline = pipeline("text-classification", model="SamLowe/roberta-base-go_emotions", top_k=3) |
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image_model = torch.hub.load('pytorch/vision', 'resnet50', pretrained=False) |
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image_model.fc = torch.nn.Linear(image_model.fc.in_features, 7) |
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image_model.load_state_dict(torch.hub.load_state_dict_from_url( |
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'https://huggingface.co/Celal11/resnet-50-finetuned-FER2013-0.001/resolve/main/pytorch_model.bin', |
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map_location=torch.device('cpu') |
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)) |
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image_model.eval() |
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image_emotions = ['Angry', 'Disgust', 'Fear', 'Happy', 'Sad', 'Surprise', 'Neutral'] |
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transform = transforms.Compose([ |
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transforms.Resize((224, 224)), |
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transforms.ToTensor() |
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]) |
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spiritual_reflections = { |
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"Sadness": "For indeed, with hardship [will be] ease. (Qur’an 94:6)", |
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"Joy": "Say, ‘In the bounty of Allah and in His mercy – in that let them rejoice.’ (Qur’an 10:58)", |
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"Fear": "And whoever fears Allah – He will make for him a way out. (Qur’an 65:2)", |
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"Anger": "Those who restrain anger and who pardon the people – Allah loves the doers of good. (Qur’an 3:134)", |
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"Surprise": "They plan, and Allah plans. Surely, Allah is the best of planners. (Qur’an 8:30)", |
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"Disgust": "Indeed, the most noble of you in the sight of Allah is the most righteous. (Qur’an 49:13)", |
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"Neutral": "Verily, in the remembrance of Allah do hearts find rest. (Qur’an 13:28)" |
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} |
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def analyze_text_emotion(text): |
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emotions = text_emotion_pipeline(text) |
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top_emotion = emotions[0]["label"] |
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reflection = spiritual_reflections.get(top_emotion, "Reflect with patience and prayer. (Qur’an 2:153)") |
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return top_emotion, reflection |
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def analyze_image_emotion(image): |
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img_tensor = transform(image).unsqueeze(0) |
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with torch.no_grad(): |
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logits = image_model(img_tensor) |
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probs = F.softmax(logits, dim=1)[0] |
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top_idx = torch.argmax(probs).item() |
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top_emotion = image_emotions[top_idx] |
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reflection = spiritual_reflections.get(top_emotion, "Reflect with patience and prayer. (Qur’an 2:153)") |
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return top_emotion, reflection |
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with gr.Blocks() as demo: |
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gr.Markdown("## 🧠 EmotionLens — AI-Powered Emotional Intelligence with Islamic Wisdom") |
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with gr.Tabs(): |
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with gr.TabItem("Single Input"): |
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with gr.Row(): |
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text_input = gr.Textbox(lines=2, placeholder="Enter text here...") |
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img_input = gr.Image(type="pil") |
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with gr.Row(): |
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submit_btn = gr.Button("Submit") |
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with gr.Column(): |
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emotion_output = gr.Textbox(label="Emotion Detection") |
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reflection_output = gr.Textbox(label="Spiritual Reflection") |
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def combined_handler(text, img): |
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if text: |
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return analyze_text_emotion(text) |
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elif img: |
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return analyze_image_emotion(img) |
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else: |
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return "No input", "Please provide text or image." |
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submit_btn.click( |
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fn=combined_handler, |
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inputs=[text_input, img_input], |
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outputs=[emotion_output, reflection_output] |
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) |
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demo.launch() |
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